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What is H2O.ai?

H2O.ai leads the way in open-source artificial intelligence and machine learning, striving to make AI available to everyone. Our advanced platforms are tailored for enterprise use and assist numerous data scientists within over 20,000 organizations globally. By empowering businesses in various fields, including finance, insurance, healthcare, telecommunications, retail, pharmaceuticals, and marketing, we are playing a crucial role in cultivating a new generation of companies that leverage AI to produce real value and innovation in the modern market. Our dedication to democratizing technology is not just about accessibility; it's about reshaping the operational landscape across industries to encourage growth and resilience in a rapidly evolving environment. Through these efforts, we aspire to redefine the future of work and enhance productivity across sectors.

What is Azure Machine Learning?

Optimize the complete machine learning process from inception to execution. Empower developers and data scientists with a variety of efficient tools to quickly build, train, and deploy machine learning models. Accelerate time-to-market and improve team collaboration through superior MLOps that function similarly to DevOps but focus specifically on machine learning. Encourage innovation on a secure platform that emphasizes responsible machine learning principles. Address the needs of all experience levels by providing both code-centric methods and intuitive drag-and-drop interfaces, in addition to automated machine learning solutions. Utilize robust MLOps features that integrate smoothly with existing DevOps practices, ensuring a comprehensive management of the entire ML lifecycle. Promote responsible practices by guaranteeing model interpretability and fairness, protecting data with differential privacy and confidential computing, while also maintaining a structured oversight of the ML lifecycle through audit trails and datasheets. Moreover, extend exceptional support for a wide range of open-source frameworks and programming languages, such as MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R, facilitating the adoption of best practices in machine learning initiatives. By harnessing these capabilities, organizations can significantly boost their operational efficiency and foster innovation more effectively. This not only enhances productivity but also ensures that teams can navigate the complexities of machine learning with confidence.

Media

Media

Integrations Supported

MLflow
Microsoft Azure
Superwise
BentoML
Datatron
FeatureByte
HPE Ezmeral
Vertica
witboost

Integrations Supported

MLflow
Microsoft Azure
Superwise
APERIO DataWise
Azure Database for MariaDB
Azure Kinect DK
BotCore
Evvox
Kedro
Microsoft Intelligent Data Platform
ModelOp
Visual Studio Code

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

Windows

Supported Platforms

SaaS

Customer Service / Support

Standard Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

H2O.ai

Date Founded

2011

Company Location

United States

Company Website

www.h2o.ai

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/products/machine-learning/

Categories and Features

AI Insurance

Not specified

Artificial Intelligence

For Healthcare
Machine Learning
Predictive Analytics
Process/Workflow Automation
Virtual Personal Assistant (VPA)

Data Science

Not specified

Deep Learning

Convolutional Neural Networks
Document Classification
ML Algorithm Library
Model Training
Visualization

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Visualization

ML Model Deployment

Not specified

ML Model Management

Not specified

Categories and Features

AI Development

Not specified

AI Governance

Not specified

AI Infrastructure

Not specified

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Machine Learning

Predictive Modeling

ML Model Deployment

Not specified

ML Model Management

Not specified

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